Brian Burns Email & Phone Number

Chicago, Illinois, United States

Catonsville, Md, Us

Seattle, Washington, Us

Supporting AI/ML Initiatives in Merchandising, E-commerce & Fraud organizations.

Atlanta, Georgia , Us

Advise the Georgia Tech M.S. in Analytics program on industry needs and curriculum applicabilityThe MS Analytics Advisory Board is a select group of analytics executives and professionals who help ensure that the content of the degree meets the needs of business and industry, and that the curriculum gives our students the skills and knowledge they need to excel as analytics professionals.https://analytics.gatech.edu/

San Francisco, California, Us

Lead for Levi’s AI/ML initiatives in E-commerce. Founded Generative AI features @ Levi's. Currently leading a dynamic 12-member, cross-functional team at Levi Strauss focused on AI applications in e-commerce. Concurrently, I established the Levi’s Generative AI Working Group which marks a significant stride towards integrating cutting-edge Generative AI technologies throughout the organization. My efforts are centered on developing strategic partnerships to bolster AI functionalities, emphasizing scalability and innovation. Achievements:• Engineered a strategy that bolstered annual revenue by $5M and cut recurring costs by $1.5M through an overhaul of the product recommendation system, leveraging modern ML technologies for innovative approaches to New Arrivals and complementary products.• Slashed go-to-market lead times by 60%, expediting production changes and enhancing impact by fostering technical partner collaborations, revising API policies, and streamlining pre-release assessments.• Spearheaded the creation of a proactive error detection process, notably improving site performance and user experience by promptly addressing product data inaccuracies.• Launched the Generative AI Working Group at Levi’s at no cost by orchestrating a seminal hackathon, securing Google sponsorship, and fostering valuable partnerships.

Seattle, Washington, Us

Led development of product and (Forbes recognized) outfit recommendation systems features.As a Data Science & Analytics Manager at Nordstrom, I led a team of six dedicated data scientists and analysts, focusing on enhancing our recommendation systems and digital services through deep learning. My tenure was marked by the development of customer-centric solutions and the creation of a deep learning-based outfit styling service, aimed at elevating client experiences and engagement. My strategic vision and implementation of advanced analytical strategies have significantly improved product recommendation performance and the customer experience.Achievements:• Exceeded organizational goals by extending product catalog coverage to over 90% with AI-generated outfits, significantly enhancing the shopping experience.• Doubled spending and quadrupled engagement among premium clients during the Anniversary Sale through the introduction of a hyper-personalized e-commerce experience.• Innovated a machine learning-driven stylist-customer matching system at Trunk Club, increasing monthly revenue by $5M and enriching stylist satisfaction through more diverse assignments and higher commissions.

Seattle, Washington, Us

Architected and built NLP & machine learning models for product understanding and match-making.In my role as Senior Data Scientist at Trunk Club (a Nordstrom subsidiary), I led pioneering initiatives in multi-modal personalization and customer recommendations, leveraging advanced neural network-based solutions. My expertise in Natural Language Processing (NLP) enabled the automation of sentiment analysis and product mentions in customer reviews to the entity level, significantly enhancing the personalization of customer experiences. I spearheaded the development of a machine learning system for matching customers with stylists, enhancing the customer experience and the bottom line. My commitment to excellence involved rigorous testing and validation of AI/ML models to ensure their effectiveness and scalability across our operations.Achievements:• Developed a customer-stylist matching system that increased annual revenue by $5 million, significantly boosting customer satisfaction and loyalty.• Implemented a high-fidelity, custom Named Entity Recognition (NER) process to accurately parse customer reviews, providing nuanced insights into customer sentiment at the entity level and improving product understanding.• Enhanced the item similarity recommendation feature, resulting in a 5% increase in the Add to Bag rate and overall views, by creating a multi-modal product representation.

Chicago, Illinois, Us

Led project teams to optimize wind turbine productivity and predict maintenance events for large fleets.At Uptake, I developed machine learning systems for anomaly detection, failure prediction, and performance monitoring, notably within a fleet of over 400 wind turbines. My efforts were pivotal in creating productivity-enhancing ML models tailored for the wind energy sector. This initiative set new benchmarks in predictive maintenance and operational insights. My innovative spirit was also demonstrated through my significant contributions to patenting groundbreaking ML systems.Achievements:• Developed and deployed anomaly detection and supervised machine learning models for anomaly detection, failure prediction and performance monitoring on large scale IoT sensor data.• Patented a method to recalibrate wind turbine direction data remotely, leveraging historical weather and sensor data, thus enhancing monitoring functionality.• Led the Open Source community (see github.com/uptake)

Chicago, Illinois, Us

Founded Industrial Fluid Analytics and Wind Turbine Productivity ML Products.Achievements:• Initiated and developed Uptake’s fluids analysis product offering, using machine learning to predict engine wear and component failures, establishing a new product line.• Patented a interactive, semi-supervised machine learning approach to predict machine component failures from extremely noisy signals• Being a founding member of Uptake’s Wind Energy team, I influenced product direction to extend to productivity in addition to prediction of major failure events• Mentored social sector data professionals through Uptake.org's Data Fellows Program• Contributed to open source software, including founding pkgnet, an R package for analyzing R packages using network theory

Washington, D.C., Us

Optimized spend and capacity for $3B network, reducing cost and significantly improving service.As a Senior Operations Research Analyst at USPS, I led the optimization of a $3B air transportation network, employing advanced operations research and forecasting methods to enhance efficiency and reduce costs. My work involved collaborating with nationwide teams to improve the delivery performance of priority products, focusing on timeliness and reliability. Through the analysis of extensive datasets, I provided strategic insights that guided logistics and network management decisions. I also played a key role in developing and refining analytical models to predict operational outcomes and identify improvement areas.Achievements:• Refined the Air Transportation network planning forecasting and optimization process, achieving a 3% improvement in on-time delivery of Priority mail and a $6M reduction in operating costs.• Accessed the impact of proposed processing and transportation network changes to service levels and total network cost. • Streamlined the planning process across multiple contracts

Washington, D.C., Us

Led a team of eight in the strategic design of multibillion dollar mail processing and transportation networks.

Washington, D.C., Us

Streamlined major equipment relocation & led Network Analytics support for Five Day Delivery.• Designed and implemented a national equipment relocation approval and execution workflow overseeing 6000+ high value pieces of equipment.• Led the Network Analytics support to Five Day Delivery preparations (since cancelled).

Washington, D.C., Us

Washington, D.C., Us

Chicago, Illinois, Us

Master’S Degree, Analytics

B.S., Enterprise Systems Engineering